Robust segmentation of nucleus in histopathology images via mask R-CNN

Xinpeng Xie; Yuexiang Li; Menglu Zhang; Linlin Shen

doi:10.1007/978-3-030-11723-8_43

Robust segmentation of nucleus in histopathology images via mask R-CNN

Xinpeng Xie, Yuexiang Li, Menglu Zhang, Linlin Shen

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

17 Citations (Scopus)

Abstract

Nuclei segmentation plays an import role in histopathology images analysis. Deep learning approaches have shown its strength for histopathology images processing in various studies. In this paper, we proposed a novel deep learning framework for automatic nuclei segmentation. The framework adopts the Mask R-CNN as backbone and employs structure-preserving color normalization (SPCN) and watershed for pre- and post-processing. The proposed framework achieved a Dice score of 90.46% on the validation set, which demonstrates its competing segmentation performance.

Original language	English
Title of host publication	Brainlesion
Subtitle of host publication	Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 4th International Workshop, BrainLes 2018, Held in Conjunction with MICCAI 2018, Revised Selected Papers
Editors	Farahani Keyvan, Alessandro Crimi, Spyridon Bakas, Mauricio Reyes, Theo van Walsum, Hugo Kuijf
Publisher	Springer Verlag
Pages	428-436
Number of pages	9
ISBN (Print)	9783030117221
DOIs	https://doi.org/10.1007/978-3-030-11723-8_43
Publication status	Published - 2019
Externally published	Yes
Event	4th International MICCAI Brainlesion Workshop, BrainLes 2018 held in conjunction with the Medical Image Computing for Computer Assisted Intervention Conference, MICCAI 2018 - Granada, Spain Duration: 16 Sept 2018 → 20 Sept 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11383 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	4th International MICCAI Brainlesion Workshop, BrainLes 2018 held in conjunction with the Medical Image Computing for Computer Assisted Intervention Conference, MICCAI 2018
Country/Territory	Spain
City	Granada
Period	16/09/18 → 20/09/18

Keywords

Deep learning
Instance segmentation
Nuclei segmentation
SPCN

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-11723-8_43

Cite this

Xie, X., Li, Y., Zhang, M., & Shen, L. (2019). Robust segmentation of nucleus in histopathology images via mask R-CNN. In F. Keyvan, A. Crimi, S. Bakas, M. Reyes, T. van Walsum, & H. Kuijf (Eds.), Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 4th International Workshop, BrainLes 2018, Held in Conjunction with MICCAI 2018, Revised Selected Papers (pp. 428-436). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11383 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-11723-8_43

Xie, Xinpeng ; Li, Yuexiang ; Zhang, Menglu et al. / Robust segmentation of nucleus in histopathology images via mask R-CNN. Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 4th International Workshop, BrainLes 2018, Held in Conjunction with MICCAI 2018, Revised Selected Papers. editor / Farahani Keyvan ; Alessandro Crimi ; Spyridon Bakas ; Mauricio Reyes ; Theo van Walsum ; Hugo Kuijf. Springer Verlag, 2019. pp. 428-436 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{02008935fdf14ee9844b3f656498cc29,

title = "Robust segmentation of nucleus in histopathology images via mask R-CNN",

abstract = "Nuclei segmentation plays an import role in histopathology images analysis. Deep learning approaches have shown its strength for histopathology images processing in various studies. In this paper, we proposed a novel deep learning framework for automatic nuclei segmentation. The framework adopts the Mask R-CNN as backbone and employs structure-preserving color normalization (SPCN) and watershed for pre- and post-processing. The proposed framework achieved a Dice score of 90.46% on the validation set, which demonstrates its competing segmentation performance.",

keywords = "Deep learning, Instance segmentation, Nuclei segmentation, SPCN",

author = "Xinpeng Xie and Yuexiang Li and Menglu Zhang and Linlin Shen",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 4th International MICCAI Brainlesion Workshop, BrainLes 2018 held in conjunction with the Medical Image Computing for Computer Assisted Intervention Conference, MICCAI 2018 ; Conference date: 16-09-2018 Through 20-09-2018",

year = "2019",

doi = "10.1007/978-3-030-11723-8_43",

language = "English",

isbn = "9783030117221",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "428--436",

editor = "Farahani Keyvan and Alessandro Crimi and Spyridon Bakas and Mauricio Reyes and {van Walsum}, Theo and Hugo Kuijf",

booktitle = "Brainlesion",

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Xie, X, Li, Y, Zhang, M & Shen, L 2019, Robust segmentation of nucleus in histopathology images via mask R-CNN. in F Keyvan, A Crimi, S Bakas, M Reyes, T van Walsum & H Kuijf (eds), Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 4th International Workshop, BrainLes 2018, Held in Conjunction with MICCAI 2018, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11383 LNCS, Springer Verlag, pp. 428-436, 4th International MICCAI Brainlesion Workshop, BrainLes 2018 held in conjunction with the Medical Image Computing for Computer Assisted Intervention Conference, MICCAI 2018, Granada, Spain, 16/09/18. https://doi.org/10.1007/978-3-030-11723-8_43

Robust segmentation of nucleus in histopathology images via mask R-CNN. / Xie, Xinpeng; Li, Yuexiang; Zhang, Menglu et al.
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 4th International Workshop, BrainLes 2018, Held in Conjunction with MICCAI 2018, Revised Selected Papers. ed. / Farahani Keyvan; Alessandro Crimi; Spyridon Bakas; Mauricio Reyes; Theo van Walsum; Hugo Kuijf. Springer Verlag, 2019. p. 428-436 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11383 LNCS).

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Robust segmentation of nucleus in histopathology images via mask R-CNN

AU - Xie, Xinpeng

AU - Li, Yuexiang

AU - Zhang, Menglu

AU - Shen, Linlin

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2019.

PY - 2019

Y1 - 2019

N2 - Nuclei segmentation plays an import role in histopathology images analysis. Deep learning approaches have shown its strength for histopathology images processing in various studies. In this paper, we proposed a novel deep learning framework for automatic nuclei segmentation. The framework adopts the Mask R-CNN as backbone and employs structure-preserving color normalization (SPCN) and watershed for pre- and post-processing. The proposed framework achieved a Dice score of 90.46% on the validation set, which demonstrates its competing segmentation performance.

AB - Nuclei segmentation plays an import role in histopathology images analysis. Deep learning approaches have shown its strength for histopathology images processing in various studies. In this paper, we proposed a novel deep learning framework for automatic nuclei segmentation. The framework adopts the Mask R-CNN as backbone and employs structure-preserving color normalization (SPCN) and watershed for pre- and post-processing. The proposed framework achieved a Dice score of 90.46% on the validation set, which demonstrates its competing segmentation performance.

KW - Deep learning

KW - Instance segmentation

KW - Nuclei segmentation

KW - SPCN

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SN - 9783030117221

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Brainlesion

A2 - Keyvan, Farahani

A2 - Crimi, Alessandro

A2 - Bakas, Spyridon

A2 - Reyes, Mauricio

A2 - van Walsum, Theo

A2 - Kuijf, Hugo

PB - Springer Verlag

T2 - 4th International MICCAI Brainlesion Workshop, BrainLes 2018 held in conjunction with the Medical Image Computing for Computer Assisted Intervention Conference, MICCAI 2018

Y2 - 16 September 2018 through 20 September 2018

ER -

Xie X, Li Y, Zhang M, Shen L. Robust segmentation of nucleus in histopathology images via mask R-CNN. In Keyvan F, Crimi A, Bakas S, Reyes M, van Walsum T, Kuijf H, editors, Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 4th International Workshop, BrainLes 2018, Held in Conjunction with MICCAI 2018, Revised Selected Papers. Springer Verlag. 2019. p. 428-436. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-11723-8_43

Robust segmentation of nucleus in histopathology images via mask R-CNN

Abstract

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Keywords

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